Enterprises of all types are interested in improving their recipes in order to give the consumer the best possible quality. This can only be achieved when clarity prevails about the raw materials used and the interrelation of the individual ingredients is known. A new method to determine the taste interaction between the individual components in our nutrition is currently being tested at ttz Bremerhaven in the KosaDat project funded by the Federal Ministry of Economics and Technology.
Behind the project idea is the development of a method for the computer-assisted prediction of sensory parameters such as taste, smell, and texture, as well as consumer acceptance. This should be made possible solely through knowledge about the chemical composition of a product. Dark chocolate is the consortium's first test model. The objective of the project is to predict market-relevant and objective sensory quality factors of raw materials, as well as of intermediate and end products, with the aid of data synthesis from chemical analysis and human sensory assessment. KosaDat is the abbreviation of the project's full name, which is "Correlation of Sensory and Analytical Data".
An objective measuring method with which precise quality profiles can be produced which can be rapidly interpreted helps both consumers and manufacturers: Both can hope that quality tests provide more accurate information. There is a heightened demand, above all in the framework of quality control, for instrumental measuring methods which can permit a quality and acceptance assessment profile under consideration of human sensory data which is precise and can be quickly interpreted.
In order to be able to make statistically verified statements about the correlation of e. g. the food chemistry and sensory profiles, a large data set with as many different production stages as possible must be generated. All chemical and sensory measurement results are automatically entered into a database system. Using methods taken from the field of artificial intelligence, a sub-topic of informatics which is concerned with the automation of intelligent behaviour, the data sets keyed into the database system are processed in such a way that interconnected substance and sensory patterns can be automatically identified.
The IT processes applied learn the pattern recognition first of all through chocolate samples, the chemical and sensory profiles of which are known. This makes a continuous improvement of the process possible in order in the end to predict reliably the quality of the chocolate, consumer acceptance, as well as sensory perception solely on the basis of the chemical profile.
COMPAMED.de; Source: ttz Bremerhaven